NSF Break-out Group: Medical Informatics - PowerPoint PPT Presentation

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NSF Break-out Group: Medical Informatics

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Applicability to a large class of medical problems ... Textual, visual, & spatiotemporal. Environment. Requires privacy & security measures ... – PowerPoint PPT presentation

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Title: NSF Break-out Group: Medical Informatics


1
NSF Break-out GroupMedical Informatics
  • Coordinator Wanda Pratt
  • Scribe Betty Salzberg

2
High-Level Challenge
  • The balancing act
  • Medically useful
  • Informatics research challenge not service!
  • Win-win collaborations

3
NSF Strengths over NIH
  • Non-disease specific
  • Broad perspective
  • Applicability to a large class of medical
    problems
  • Further fundamental research in Information
    Data Management
  • Innovative, long-term, risky vision

4
Characteristics of Biomedical Domain
  • Data, Information, Knowledge
  • Voluminous
  • Dirty, biased, based on implicit assumptions
  • Uncertain
  • Dynamic
  • Long lived
  • Textual, visual, spatiotemporal
  • Environment
  • Requires privacy security measures
  • Life critical
  • Busy users
  • Different types of users
  • (e.g., physicians, nurses, biologists,
    technicians, patients, etc.)

5
Implications for Research Directions
  • Spans all CISE themes
  • Ontologies
  • Data information integration
  • Knowledge discovery and analysis
  • Human-computer interaction
  • Software engineering

6
Ontologies
  • Development by domain experts
  • Maintenance as knowledge changes
  • Connected to data and information that support it
  • Support of multiple perspectives

7
Information Integration
  • Diversity
  • Systems to process and store information
  • Sources of information
  • Types of information (text, sensor data, images,
    sound, etc.)
  • High documentation needs
  • Links to sources
  • Assumptions of sources
  • Privacy and security regulations

8
Knowledge Discovery and Analysis
  • Processing large volumes
  • Finding useful patterns
  • Detecting and dealing with redundancy
  • Accounting for uncertainty
  • Showing connections
  • Revisiting old information/data when we have new
    knowledge

9
Human-Computer Interaction Software Engineering
  • Spans everything
  • Ontologies
  • Information integration
  • Knowledge discovery and analysis

10
Recommendations for NSF
  • Funding for overhead of data cleaning
    management
  • Funding for programmers
  • Funding for biomedical collaborators
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